Web: http://arxiv.org/abs/2205.15827

Sept. 16, 2022, 1:12 a.m. | Marnix Suilen, Thiago D. Simão, David Parker, Nils Jansen

cs.LG updates on arXiv.org arxiv.org

Markov decision processes (MDPs) are formal models commonly used in
sequential decision-making. MDPs capture the stochasticity that may arise, for
instance, from imprecise actuators via probabilities in the transition
function. However, in data-driven applications, deriving precise probabilities
from (limited) data introduces statistical errors that may lead to unexpected
or undesirable outcomes. Uncertain MDPs (uMDPs) do not require precise
probabilities but instead use so-called uncertainty sets in the transitions,
accounting for such limited data. Tools from the formal verification community
efficiently …

arxiv decision markov processes

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